• Journal of Astronomy and Space Sciences
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• 제22권4호
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• pp.501-512
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• 2005

This research supposed when a fictitious KSIV-I space launch vehicle launches from NARO space center. This compared and analyzed the results from real-time trajectory estimation using the Extended Kalman Filter and the Unscented Kalman Filter. A virtual trajectory and observation data are generated for the fictitious KSLV-I and three measurement radars. The performances of both Otters are compared for several simulations with small initial errors, large initial errors, 20Hz and 10Hz data rate. The results show that the Unscented Kalman Filter yields faster convergence and more accurate than the Extended Kalman Filter for the cases with larger initial error and slower data rate conditions.

• Journal of The Geomorphological Association of Korea
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• 제20권4호
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• pp.85-99
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• 2013

The objective of this paper is to analyze the spatial distribution of errors in the DEM generated using waterlines from multi-temporal remote sensing data and to assess flood vulnerability. Unlike conventional research in which only global statistics of errors have been generated, this paper tries to quantitatively analyze the spatial distribution of errors from a probabilistic viewpoint using geostatistical simulation. The initial DEM in Baramarae tidal flats was generated by corrected tidal level values and waterlines extracted from multi-temporal Landsat data in 2010s. When compared with the ground measurement height data, overall the waterline-based DEM underestimated the actual heights and local variations of the errors were observed. By applying sequential Gaussian simulation based on spatial autocorrelation of DEM errors, multiple alternative error distributions were generated. After correcting errors in the initial DEM with simulated error distributions, probabilities for flood vulnerability were estimated under the sea level rise scenarios of IPCC SERS. The error analysis methodology based on geostatistical simulation could model both uncertainties of the error assessment and error propagation problems in a probabilistic framework. Therefore, it is expected that the error analysis methodology applied in this paper will be effectively used for the probabilistic assessment of errors included in various thematic maps as well as the error assessment of waterline-based DEMs in tidal flats.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• 제43권3호
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• pp.213-223
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• 2015

The helicopter initial design model was established by using the latest weight estimation equations based on the Tishchenko's methodology through the study existing initial design tools. The sequential decomposition method is used to reduce analysis time in the sizing. Empirical parameters of the weight estimation equation were also extracted from numerical and regression analysis for a helicopter database. Design input and output values were compared with the RISPECT design tool. Finally, comparison of the re-design resulting for several existing helicopters was presented and showed the good agreement within less than 5% in the weight estimation and main rotor sizing. Established initial design model was proved to be effectively used as initial design tool.

• The Transactions of the Korean Institute of Power Electronics
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• 제12권1호
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• pp.65-73
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• 2007

This paper presents an on-line correction method of current measurement errors for a pure-integration-based flux estimation down to 1-Hz stator frequency. An observer-based approach is taken as one possible solution of eliminating the dc offset and the negative sequence component of unbalanced gains in the synchronous coordinate. At the same time, the positive sequence component estimation is performed by creating an error signal between a motor model reference and an estimated q-axis rotor flux established by a permanent magnet (PM) in the synchronous coordinate. The compensator utilizes a PI controller that controls the error signal to zero. The proposed technique further contains a residual error compensator to completely eliminate miscellaneous disturbances in the estimated flux. The developed algorithm has been implemented on a 1.1-kW permanent magnet synchronous motor (PMSM) drive to confirm the effectiveness of the proposed scheme.

• The Transactions of the Korean Institute of Power Electronics
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• 제10권1호
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• pp.13-20
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• 2005

This paper has proposed an algorithm for the initial pole position estimation of a permanent magnet linear synchronous motor(PMLSM). The algorithm finds the initial pole position observing the maximum values of a position generated by the new proposed two reference frames for the same force input. So, the proposed algorithm does not utilize the motor parameters and is insensitive to them. Moreover, the proposed algorithm is easily realized because the proposed method is just using PI controller

• Journal of the Institute of Electronics Engineers of Korea SP
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• 제40권2호
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• pp.11-19
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• 2003

This paper proposes an algorithm to reduce the estimation error of surface spectral-reflectance(SR) using a conventional 3-band RGB camera. In the proposed method, estimation error can be reduced by using adaptive principal components(PCs) for each color region. In order to build adaptive set of PCs, n SR populations are organized for n PC sets by using Lloyd quantizer design algorithm. Macbetch ColorCheckcer is utilized as initial representative SR values for 1485 Munsell color chips of total color population and the Munsell chips arc divided subsets and a set of corresponding adaptive PCs per each subset is organized. As a result of experiments, the proposed method showed advanced estimation performance compared to both the two 3-band PCA methods and the 5-band wiener method.

• Journal of Korean Society of Transportation
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• 제32권6호
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• pp.589-599
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• 2014

This paper analyzes the forecasting errors of traffic volumes by comparing forecasted volumes for the opening year with the observed ones in the years after the urban railway construction in the metropolitan areas. The result shows that the average inaccuracy of traffic volumes for each station was estimated at around 7.27. Based on the confirmed factors of demand estimation errors, this study seeks for an alternative method to reduce estimation errors in feasibility studies. It is noted that there is a tendency that the inaccuracy varies by regions and the longer construction period or the shorter station spacing is, the overestimation increases. If urban railway projects are proceeded as planed, therefore, the level of the inaccuracy for traffic volume forecast will be decreased. In addition, thanks to the theoretical progress, recent estimation results show higher accuracy than before. In that sense, when we introduce the new railway line, it is necessary to make an accurate and realistic demand forecast based on actual outcomes and tendency of the previous estimation. The limitation of our study is that we only cover the errors of the initial period, the opening year and deal with the exogenous variables. Further research including other variables which might be considered to cause overestimation or errors would be needed for increasing the estimation accuracy of traffic volumes.

• KIISE Transactions on Computing Practices
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• 제23권4호
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• pp.210-216
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• 2017

In the paper we propose and implement a new indoor localization system where the techniques of magnetic field based fingerprinting and pedestrian dead reckoning are combined. First, we determine a target's location by comparing acquired magnetic field values with a magnetic field map containing pre-collected field values at different locations and choosing the location having the closest value. As the target moves, we use pedestrian dead reckoning to estimate the expected moving path, reducing the maximum positioning error of the initial location. The system eliminates the problem of localization error accumulation in pedestrian dead reckoning with the help of the fingerprinting and does not require Wi-Fi AP infrastructure, enabling cost-effective localization solution.

• Journal of the Korean Geotechnical Society
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• 제35권8호
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• pp.43-56
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• 2019

This research has been conducted to suggest an estimation equation of compression index to be practically applied to the southeastern areas by finding out physical and mechanical characteristics of 229 points on the southeastern coast areas (Busan area: 78 points, Gimhae area: 103 points, Geoje area: 18 points, Changwon area: 30 points) through indoor tests and analyzing its relation to the compression index. From the results, we could not only find out correlation between natural water content, liquid limit and initial void ratio versus compression index for soft ground on each of the southeastern coast areas, but also an integrated correlation equation of the southeastern coast areas. In addition, we have performed a comparative analysis of the existing estimated equation of compression index and that found in this paper. As a result, the existing estimated equation suggested by foreign researchers has shown considerable error to be applied to the soft ground on the southeastern coast areas in Korea. The estimated equation of compression index with the water content out of the existing estimated equations has shown minimum 10.8% to maximum 48.1% of error rate, minimum 13.4% to maximum 288.5% of error rate with liquid limit or minimum 9.4% to maximum 211.4% of error rate with initial void ratio. On the other hand, error rates calculated with the estimated equations of compression index from this research have shown minimum 10.5% to maximum 13.4% with water content, minimum 11.6% to maximum 21.3 with liquid limit or minimum 7.1% to maximum 11.7% with initial void ratio, for better results than those with existing estimated equations. In addition, relation between compression index and expansion index has shown Cs = (1/5 ~ 1/12)Cc similar to the existing relation of Cs = (1/5 ~ 1/10)Cc.

• Proceedings of the KIEE Conference
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2879-2881
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• 2005

본 논문에서는 뉴로-퍼지 모델의 전제부 소속함수의 새로운 학습방법을 통한 모델링 기법을 제안한다. 모델의 크기와 학습시간을 줄이는 기법으로 클러스터링 기법을 이용한 모델의 초기 파라미터 결정 방법이 있다. 이는 클러스터링 후 이들 파라미터를 다시 모델에 적용하여 모델을 학습하는 순차적 방법으로써 모델의 학습이 끝난 후의 전제부 파라미터가 클러스터링 파라미터와 연관성을 가지지 못하는 경우가 발생하였다. 또한 오차미분 기반 학습에서는 전제부 초기치가 국부적 최적해에서 벋어나지 못하는 문제점을 가지고 있다. 본 논문에서는 자율적으로 클러스터의 수를 추정하며 이들 파라미터를 최적화하며 이를 이용하여 뉴로-퍼지 모델의 학습을 실시하는 학습기법을 제안하였다. 제안된 방법에서는 기존의 오차미분 기반 학습을 클러스터링 기반 학습으로 확장하였으며 이를 이용한 모델의 성능을 기존의 연구결과와 비교하여 우수성을 보인다.